What makes a student “employable”?

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This blog post was co-authored by Leigh-Anne Gillespie and Lindsay Hart.

Here in Canada, we find a data scientist is a wondrous, near-mythical creature. We have all heard the long list of skills required to be a data scientist. For example, software engineer Josh Wills of Slack defined a data scientist as “a person who is better at statistics than any software engineer, and better at software engineering than any statistician”. In other words, data scientists are not just number crunchers. They are also more than mere engineers. They need both skillsets, and then soft skills as well.

"A data scientist is like a wondrous, near-mythical creature"

To be job-ready, you should be comfortable solving business cases using real world “dirty” data and big data, and also be able to explain your findings. The best way to think of it is being a story-teller, because you will be presenting business insights with recommendations and defending your technical work. So how does one person have time to master all these skills?

Academic programs, internships and networks

The good news is that there has been an explosion of data analytics education programs across Canada. Since 2015, there has been a dramatic increase in Master’s programs alone, and it is the same story for post-secondary and graduate certificate programs. Master’s programs are typically developed over a three-year period in the academic cycle, so the immediate rise in analytics programs shows the level of demand for data science education. But is formal training enough?

Employers often complain that new graduates and post-graduates may not be fully ‘job-ready’, but there are ways to help students develop their skills. For example, the SAS Canada Academic Program supports teaching and research in analytics, and also connects students with companies looking to fill their analytics skills gap. It therefore helps to make students more ‘job-ready’, and also connects them with potential jobs. The Program receives over 50 job descriptions each year from clients looking for new talent. These potential employers know the quality of candidates coming through the Program is likely to be good.

Hackathons

Data competitions — or hackathons — are another way the Program can help connect students and employers. Whether over a weekend, or longer term, and built into courses, these competitions offer an opportunity for real-life programming and problem-solving experience. In April 2017, for example, SAS Canada, Deloitte, and Scotiabank partnered with Ivey Business School to host the first annual Hack the Case competition. Five of Ivey’s MSc Business Analytics students were later hired through connections made during the competition.

Five MSc Business Analytics students were hired through connections made during #hackathon. #sasacademic #DataScience Click To Tweet

Why do these competitions work so well as a recruitment exercise? Being able to see candidates in action in hackathons allows employers to see how they will react in a workplace. They allow candidates to showcase all their skills, both technical and ‘soft’. With the rate of success of standard one-to-one interviewing being little better than tossing a coin, this kind of opportunity is helpful for employers and students alike. One media outlet commented afterwards that the winning team at Hack the Case stood out because of their communication skills: they were able to explain their answer. This type of skill would not necessarily have emerged during a formal interview.

But there is even more to it. Hackathons give students a broader and more applied understanding of analytics. In other words, they actually increase their skills and experience. Datasets in hackathons are likely to be bigger than the students have previously encountered, and also have all the complexity of real-world data. These competitions therefore provide a unique platform for industry to find exactly what they are looking for: individuals who can both manage and discuss the data.

New Year’s resolutions

The SAS Canada Academic Program is currently looking ahead to 2018 competitions. Three major financial institutions have already approached the team indicating their interest in acting as a data donor and recruitment partner. Next year’s competitions, in other words, are already looking strong. There is no question that companies are hungry for new talent and students are keen to participate! Contact us if you’re interested in connecting with emerging analytics talent or to learn more.

This blog post was co-authored by Leigh-Anne Gillespie and Lindsay Hart.

Learn more about careers in Analytics and how business and education come together to educate new talents in our series exploring Data Science.

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About Author

Lindsay Hart

SAS Canada Academic Program

Lindsay Hart joined SAS Canada in March 2015 as the Academic Program Coordinator. Her work focuses on developing relationships with universities and colleges across Canada to help advance the use of SAS Analytics and fill the data science skills gap. Before joining SAS, Lindsay worked as a Program Specialist for Mitacs, a national research organization building bridges between academia and industry. Lindsay has a Master of Global Affairs from the University of Toronto and a Bachelor's degree in Political Science from New York University.

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